1. Field of The Invention
The present invention relates to a method and an apparatus for converting an image signal representing an image having gradations and more particularly, to improvement in establishing highlight and/or shadow points in a gradation converter employable in a color process scanner.
2. Description of Prior Arts
As is well known in the field of color image reproduction, a color original image having gradations is photoelectrically read by a process scanner and the original image signal thus obtained is converted into a processed image signal in gradation converter provided in the process scanner. The conversion is required for obtaining a desired image expression on a medium on which the original image is reproduced, and the conversion characteristic in the gradation converter is determined in accordance with a gradation curve. The gradation curve is obtained through establishment of highlight and shadow densities on a two-dimensional coordinate plane on which the gradation curve is to be defined. The highlight and shadow densities are called "reference densities", while the points defined on the coordinate plane in accordance with the highlight and shadow densities are called "reference density points".
The highlight and shadow densities may be determined by an operator through manual operation. However, the manual determination of the gradation curve requires a skilled operator, so that many original images cannot be processed in a short time. Accordingly, automatic determination of gradation curves has been developed.
In a conventional procedure for automatic establishment of the highlight and shadow points, an input highlight density and an input shadow density for a gradation curve are determined through the procedure shown in FIG. 17.
An original to be reproduced is prescanned to provide the density of the original image for each color component for each pixel in the process step S501.
The densities for the respective color components are averaged to determine an average density for each pixel, and then an average density histogram is constructed in the process step S502.
In the process step S503, a cumulative density is calculated for each rank for each color component to provide a cumulative density histogram shown in FIG. 19. FIG. 19 shows the cumulative density histogram only for the color component R.
In the process step S504, the relative frequency of the pixels added up from the low-density rank is determined. A cumulative relative frequency histogram shown in FIG. 18 is then constructed in which the relative frequency varies from 0% to 100% with respect to the average density ranging from a minimum generated density to a maximum generated density.
In the process step S505, predetermined cumulative density appearance rates RN.sub.H, RN.sub.S corresponding to highlight and shadow points providing experimentally derived optimal gradation conversion characteristics are applied to the cumulative relative frequency histogram, to provide tentative highlight and shadow average densities D.sub.MH and D.sub.MS corresponding to the cumulative relative frequency.
The tentative highlight and shadow average densities D.sub.MH and D.sub.MS are applied to the cumulative density histograms by color component shown in FIG. 19 to provide the input highlight and shadow densities for each color component in the process step S506. The highlight and shadow points or reference density points through which the gradation curve is to be drawn are established as a function of the obtained input highlight and shadow densities and arbitrarily pre-established output highlight and shadow densities.
Unfortunately, the conventional method has drawbacks to be described below. When the original depicts a scene having a bright background or photographed against the light, the input highlight density becomes lower than a preferable level so that the reproduced image is finished darkly. When the original depicts a scene having a dark background, on the other hand, the input shadow density becomes higher so that the reproduced image is whitish.
The cause of such dark or whitish reproduced image will be described below. When the original depicts the scene having the bright background, the cumulative density histogram of FIG. 19 is affected by the bright background to have more frequent lower-density ranks. This results in a low tentative highlight average density determined from the cumulative relative frequency histogram of FIG. 18 and, accordingly, a low input highlight density obtained in the process step S506. The low input highlight density causes the gradation curve in a highlight region to be shifted toward the output shadow density since the gradation curve is produced as a function of the input highlight density. As a result, the reproduced image is finished darkly.
When the original has the dark background, the cumulative density histogram of FIG. 19 has more frequent higher-density ranks, so that the input shadow density given in the process step S506 grows high. This causes the gradation curve in a shadow region to be shifted toward the output highlight density, resulting in the whitish finish of the reproduced image obtained by the gradation conversion in accordance with the gradation curve.
Such a problem occurs also in the case where the original image includes a portion having a very low density and a certain area such as a glittering metal portion, even if the portion is not located in the background of the original image. The conventional method causes the undesired image-reproduction in which the input highlight density becomes lower than a preferable level so that the reproduced image is sometimes finished darkly or gives an impression that the entire color thereof is turbid.